Search results for: parameter selection

Authors: Saeed Karimi, Ali Behbahaninia

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In this study, the design and optimization of combined cooling, heating, and power system (CCHP) for a sustainable building are dealt with. Sustainable buildings are environmentally responsible and help us to save energy also reducing waste, pollution and environmental degradation. CCHP systems are widely used to save energy sources. In these systems, electricity, cooling, and heating are generating using just one primary energy source. The selection of the size of components based on the maximum demand of users will lead to an increase in the total cost of energy and equipment for the building complex. For this purpose, a system was designed in which the prime mover (gas turbine), heat recovery boiler, and absorption chiller are lower than the needed maximum. The difference in months with peak consumption is supplied with the help of electrical absorption chiller and auxiliary boiler (and the national electricity network). In this study, the optimum capacities of each of the equipment are determined based on Thermo economic method, in a way that the annual capital cost and energy consumption will be the lowest. The design was done for a gas turbine prime mover, and finally, the optimum designs were investigated using exergy analysis and were compared with a traditional energy supply system.

Keywords: sustainable building, CCHP, energy optimization, gas turbine, exergy, thermo-economic

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Authors: Ting Li Liu

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‘Leftover woman’ or ‘3S’ woman is the term used to describe a well-educated, high income, independent woman who is single and never married around 30 years in Chinese society. With the naming of this demographic of ‘leftover women’, their family, dating culture, mate selection and marriage attract public concern. Massive media representations of ‘leftover women’ occur daily; the research aims to present several media representations of women’s anxiety about their singlehood and related marital issues around thirty. The research triangulates two areas of media representation of ‘leftover women’: films and audience reviews on ‘Douban Movie’ website. Drawing on traditional media studies, Fairclough’s critical discourse analysis combined with multimodal techniques is applied to the research to analyze the representations of ‘leftover women’ and their implications for marital culture in China, in conjunction with a feminist perspective. The conference paper will discuss two case studies: the film ‘The last woman standing’ and ‘I Do’. Paying attention to different aspects of ‘leftover women’, the research aims to re-examine the representations of ‘leftover women’ in selected scenes, such as their age anxiety, family, marriage, dating process, careers, etc. The paper also includes public beliefs about ‘leftover women’ from online audience reviews. In conclusion, the emergence of ‘leftover women’ is a reflection of Chinese tradition’s impact on people’s lives and new changes in Chinese families and their attitude to marriage.

Keywords: leftover women, marriage, family, media culture, China

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Authors: Ahmed Boufedah Badissi, Ahmed Beroual, Farid Boursas

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This research aims to elucidate the role of coarse aggregate in influencing the fresh properties of normal-strength concrete. Specifically, it is aimed to identify the optimal gradation of coarse aggregate to enhance workability. While existing literature discusses the impact of aggregate granularity on concrete workability, more numerical data or models need to quantify the relationship between workability, granularity, and coarse aggregate shape. The main objective is to create a model that describes how coarse aggregate morphology contributes to fresh concrete properties. To investigate the effect of coarse aggregate gradation on Normal Strength Concrete (NSC) workability, various combinations of coarse aggregates (4/22.4 mm) were produced in the laboratory, utilizing three elementary classes: finer coarse aggregate 4/8 mm (Fca), medium coarse aggregate 8/16 mm (Mca), and coarser coarse aggregate 16/22.4 mm (Cca). We introduced a factor, FCR (Finer to Coarser coarse aggregate Ratio), as a numerical parameter to provide a quantitative evaluation and more detailed results analysis. Quantitative characterization parameters for coarse aggregate morphology were established, exploring the influence of particle size distribution, specific surface, and aggregate shape on workability. The research findings are significant for establishing correlations between coarse aggregate morphology and concrete properties. FCR emerges as a valuable tool for predicting the impact of aggregate gradation variations on concrete. The results of this study create a valuable database for construction professionals and concrete producers, affirming that the fresh properties of NSC are intricately linked to coarse aggregate morphology, particularly gradation.

Keywords: morphology, coarse aggregate, workability, fresh properties, gradation

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Authors: Y. H. Wang, C. C. Hsieh

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Good service design can increase organization revenue and consumer satisfaction while reducing labor and time costs. The problems facing consumers in the original serve model for eyewear and optical industry includes the following issues: 1. Insufficient information on eyewear products 2. Passively dependent on recommendations, insufficient selection 3. Incomplete records on progression of vision conditions 4. Lack of complete customer records. This study investigates the case of Kobayashi Optical, applying the Theory of Inventive Problem Solving (TRIZ) to develop innovative solutions for eyewear and optical industry. Analysis results raise the following conclusions and management implications: In order to provide customers with improved professional information and recommendations, Kobayashi Optical is suggested to establish customer purchasing records. Overall service efficiency can be enhanced by applying data mining techniques to analyze past consumer preferences and purchase histories. Furthermore, Kobayashi Optical should continue to develop a 3D virtual trial service which can allow customers for easy browsing of different frame styles and colors. This 3D virtual trial service will save customer waiting times in during peak service times at stores.

Keywords: theory of inventive problem solving (TRIZ), service design, augmented reality (AR), eyewear and optical industry

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Hamed Yousefi, Farnaz Mohammadi, Niloufar Mirian, Navid Amini

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Investigating possible capacities of visual functions where adapted mechanisms can enhance the capability of sports trainees is a promising area of research, not only from the cognitive viewpoint but also in terms of unlimited applications in sports training. In this paper, the visual evoked potential (VEP) and event-related potential (ERP) signals of amateur and trained volleyball players in a pilot study were processed. Two groups of amateur and trained subjects are asked to imagine themselves in the state of receiving a ball while they are shown a simulated volleyball field. The proposed method is based on a set of time-frequency features using algorithms such as Gabor filter, continuous wavelet transform, and a multi-stage wavelet decomposition that are extracted from VEP signals that can be indicative of being amateur or trained. The linear discriminant classifier achieves the accuracy, sensitivity, and specificity of 100% when the average of the repetitions of the signal corresponding to the task is used. The main purpose of this study is to investigate the feasibility of a fast, robust, and reliable feature/model determination as a neurofeedback parameter to be utilized for improving the volleyball players’ performance. The proposed measure has potential applications in brain-computer interface technology where a real-time biomarker is needed.

Keywords: visual evoked potential, time-frequency feature extraction, short-time Fourier transform, event-related spectrum potential classification, linear discriminant analysis

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Authors: Youssouf Benmeriem

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Shear strength of sandy soils has been considered as the important parameter to study the stability of different civil engineering structures when subjected to monotonic, cyclic and earthquake loading conditions. The proposed research investigated the effect of grading characteristics on the shear strength and mechanical behavior of granular classes of sands mixed with silt in loose and dense states (Dr = 15% and 90%). The laboratory investigation aimed at understanding the extent or degree at which shear strength of sand-silt mixture soil is affected by its gradation under static loading conditions. For the purpose of clarifying and evaluating the shear strength characteristics of sandy soils, a series of Casagrande shear box tests were carried out on different reconstituted samples of sand-silt mixtures with various gradations. The soil samples were tested under different normal stresses (100, 200 and 300 kPa). The results from this laboratory investigation were used to develop insight into the shear strength response of sand and sand-silt mixtures under monotonic loading conditions. The analysis of the obtained data revealed that the grading characteristics (D10, D50, Cu, ESR, and MGSR) have significant influence on the shear strength response. It was found that shear strength can be correlated to the grading characteristics for the sand-silt mixture. The effective size ratio (ESR) and mean grain size ratio (MGSR) appear as pertinent parameters to predict the shear strength response of the sand-silt mixtures for soil gradation under study.

Keywords: grading characteristics, granular classes of sands, mechanical behavior, sand-silt, shear strength

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Authors: Norshima Humaidi, Saif Hussein Abdallah Alghazo

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Cybersecurity threat have become a serious issue recently, and one of the cause is because human error, which is usually constituted by carelessness, ignorance, and failure to practice cybersecurity behaviour adequately. Using a data from a quantitative survey, Partial Least Squares-Structural Equation Modelling (PLS-SEM) analysis was used to determine the factors that affect cybersecurity protective behaviour (CPB). This study adapts cybersecurity protective behaviour model by focusing on two constructs that can enhance CPB: manager’s information security competencies (MISI) and procedural information security countermeasure (PCM) awareness. Theory of leadership competencies were adapted to measure user’s perception towards competencies among security managers/leader in the organization. Confirmatory factor analysis (CFA) testing shows that all the measurement items of each constructs were adequate in their validity individually based on their factor loading value. Moreover, each constructs are valid based on their parameter estimates and statistical significance. The quantitative research findings show that PCM awareness strongly influences CPB compared to MISI. Meanwhile, MISI was significantlyPCM awarenss. This study believes that the research findings can contribute to human behaviour in IS studies and are particularly beneficial to policy makers in improving organizations’ strategic plans in information security, especially in this new era. Most organizations spend time and resources to provide and establish strategic plans of information security; however, if employees are not willing to comply and practice information security behaviour appropriately, then these efforts are in vain.

Keywords: cybersecurity, protection behaviour, information security, information security competencies, countermeasure awareness

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Authors: S. J. M. Mohd Saleh, S. Guo

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Composite materials have become an important option for the primary structure of aircraft due to their design flexibility and ability to improve the overall performance. At present, the option for composite usage in aircraft component is largely based on experience, knowledge, benchmarking and partly market driven. An inevitable iterative design during the design stage and validation process will increase the development time and cost. This paper aims at presenting the correlation between laminate and composite thin-wall beam structure, which contains the theoretical and numerical investigations on stiffness estimation of composite aerostructures with applications to aircraft wings. Classical laminate theory and thin-walled beam theory were applied to define the correlation between 1-dimensional composite laminate and 2-dimensional composite beam structure, respectively. Then FE model was created to represent the 3-dimensional structure. A detailed study on stiffness matrix of composite laminates has been carried out to understand the effects of stacking sequence on the coupling between extension, shear, bending and torsional deformation of wing box structures for 1-dimensional, 2-dimensional and 3-dimensional structures. Relationships amongst composite laminates and composite wing box structures of the same material have been developed in this study. These correlations will be guidelines for the design engineers to predict the stiffness of the wing box structure during the material selection process and laminate design stage.

Keywords: aircraft design, aircraft structures, classical lamination theory, composite structures, laminate theory, structural design, thin-walled beam theory, wing box design

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Authors: Kemka Ihemelandu, Chukwuemeka Ihemelandu

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Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes, a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone, have increasingly been recognized as a problem.Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN)models. CNN models are prone to biased output due to biases in the dataset used to train them. Our aim in this study was the optimization of convolutional neural network algorithms to mitigate bias in the automated diagnosis of melanoma. We hypothesized that our proposed training algorithms based on a data augmentation method to optimize the diagnostic accuracy of a CNN classifier by generating new training samples from the original ones will reduce bias in the automated diagnosis of melanoma. We applied geometric transformation, including; rotations, translations, scale change, flipping, and shearing. Resulting in a CNN model that provided a modifiedinput data making for a model that could learn subtle racial features. Optimal selection of the momentum and batch hyperparameter increased our model accuracy. We show that our augmented model reduces bias while maintaining accuracy in the automated diagnosis of melanoma.

Keywords: bias, augmentation, melanoma, convolutional neural network

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Authors: Rafael Santos Fischer, Aloísio Leoni Schmid, Amanda Dalla-Bonna

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The life cycle analysis and the energy life cycle analysis are useful design support tools when sustainability becomes imperative. The final phase of buildings life cycle is probably the least known, on which less knowledge is available. In the Brazilian building industry, the lifespan of a building design rarely is treated as a definite design parameter. There is rather a common sense attitude to take any building demands as permanent, and to take for granted that buildings solutions are durable and solid. Housing, being a permanent issue in any society, presents a real challenge to the choice of a design lifespan. In Brazilian history, there was a contrast of the native solutions of collective, non-durable houses built by several nomadic tribes, and the stone and masonry buildings introduced by the sedentary Portuguese conquerors. Durable buildings are commonly associated with welfare. However, social dynamics makes traditional families of both parents and children be just one of several possible arrangements. In addition, a more liberal attitude towards family leads to an increase in the number of people living in alternative arrangements. Japan is an example of country where houses have been made intentionally ephemeral since the half of 20th century. The present article presents the development of a flexible housing design solution on the basis of the Design Science Research approach. A comparison in terms of energy life cycle shows how flexibility and dematerialization may point at a feasible future for housing policies in Brazil.

Keywords: adaptability, adaptable building, embodied energy, life cyclce analysis, social housing

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Authors: Anjela Koblischka-Veneva, Michael R. Koblischka

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In this contribution, the Transmission-Kikuchi Diffraction (TKD, or sometimes called t-EBSD) is applied to bulk, melt-grown YBa₂Cu₃O₇ (YBCO) superconductors prepared by the MTMG (melt-textured melt-grown) technique and the infiltration growth (IG) technique. TEM slices required for the analysis were prepared by means of Focused Ion-Beam (FIB) milling using mechanically polished sample surfaces, which enable a proper selection of the interesting regions for investigations. The required optical transparency was reached by an additional polishing step of the resulting surfaces using FIB-Ga-ion and Ar-ion milling. The improved spatial resolution of TKD enabled the investigation of the tiny YBa₂Cu₃O₅ (Y-211) particles having a diameter of about 50-100 nm embedded within the YBCO matrix and of other added secondary phase particles. With the TKD technique, the microstructural properties of the YBCO matrix are studied in detail. It is observed that the matrix shows the effects of stress/strain, depending on the size and distribution of the embedded particles, which are important for providing additional flux pinning centers in such superconducting bulk samples. Using the Kernel Average Misorientation (KAM) maps, the strain induced in the superconducting matrix around the particles, which increases the flux pinning effectivity, can be clearly revealed. This type of analysis of the EBSD/TKD data is, therefore, also important for other material systems, where nanoparticles are embedded in a matrix.

Keywords: transmission Kikuchi diffraction, EBSD, TKD, embedded particles, superconductors YBa₂Cu₃O₇

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Authors: Syed Ahsan, Saleh Alshomrani, Ishtiaq Rasool, Ali Hassan

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In this oral presentation, we will provide an overview of the technical and semantic architecture of a desert border security and critical infrastructure protection security system. Modern border security systems are designed to reduce the dependability and intrusion of human operators. To achieve this, different types of sensors are use along with video surveillance technologies. Application of these technologies in a harsh desert environment of Saudi Arabia poses unique challenges. Environmental and geographical factors including high temperatures, desert storms, temperature variations and remoteness adversely affect the reliability of surveillance systems. To successfully implement a reliable, effective system in a harsh desert environment, the following must be achieved: i) Selection of technology including sensors, video cameras, and communication infrastructure that suit desert environments. ii) Reduced power consumption and efficient usage of equipment to increase the battery life of the equipment. iii) A reliable and robust communication network with efficient usage of bandwidth. Also, to reduce the expert bottleneck, an ontology-based intelligent information systems needs to be developed. Domain knowledge unique and peculiar to Saudi Arabia needs to be formalized to develop an expert system that can detect abnormal activities and any intrusion.

Keywords: border security, sensors, abnormal activity detection, ontologies

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Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

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Authors: G. C. Jadeja, M. A. Desai, D. R. Bhatt, J. K. Parikh

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Green extraction techniques are fast paving ways into various industrial sectors due to the stringent governmental regulations leading to the banning of toxic chemicals’ usage and also due to the increasing health/environmental awareness. The present work describes the ionic liquids based sonication method for selectively extracting patchoulol from the leaves of patchouli. 1-Butyl-3-methylimidazolium tetrafluoroborate ([Bmim]BF4) and N,N,N,N’,N’,N’-Hexaethyl-butane-1,4-diammonium dibromide (dicationic ionic liquid - DIL) were selected for extraction. Ultrasound assisted ionic liquid extraction was employed considering concentration of ionic liquid (4–8 %, w/w), ultrasound power (50–150 W for [Bmim]BF4 and 20–80 W for DIL), temperature (30–50 oC) and extraction time (30–50 min) as major parameters influencing the yield of patchoulol. Using the Taguchi method, the parameters were optimized and analysis of variance (ANOVA) was performed to find the most influential factor in the selected extraction method. In case of [Bmim]BF4, the optimum conditions were found to be: 4 % (w/w) ionic liquid concentration, 50 W power, 30 oC temperature and extraction time of 30 min. The yield obtained under the optimum conditions was 3.99 mg/g. In case of DIL, the optimum conditions were obtained as 6 % (w/w) ionic liquid concentration, 80 W power, 30 oC temperature and extraction time of 40 min, for which the yield obtained was 4.03 mg/g. Temperature was found to be the most significant factor in both the cases. Extraction time was the insignificant parameter while extracting the product using [Bmim]BF4 and in case of DIL, power was found to be the least significant factor affecting the process. Thus, a green method of recovering patchoulol is proposed.

Keywords: green extraction, ultrasound, patchoulol, ionic liquids

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Authors: Korosh Khorshidi, Mohammad Khodadadi

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In this paper, exact close form solution for out of plate free flexural vibration of moderately thick rectangular nanoplates are presented based on nonlocal modified trigonometric shear deformation theory, with assumptions of the Levy's type boundary conditions, for the first time. The aim of this study is to evaluate the effect of small-scale parameters on the frequency parameters of the moderately thick rectangular nano-plates. To describe the effects of small-scale parameters on vibrations of rectangular nanoplates, the Eringen theory is used. The Levy's type boundary conditions are combination of six different boundary conditions; specifically, two opposite edges are simply supported and any of the other two edges can be simply supported, clamped or free. Governing equations of motion and boundary conditions of the plate are derived by using the Hamilton’s principle. The present analytical solution can be obtained with any required accuracy and can be used as benchmark. Numerical results are presented to illustrate the effectiveness of the proposed method compared to other methods reported in the literature. Finally, the effect of boundary conditions, aspect ratios, small scale parameter and thickness ratios on nondimensional natural frequency parameters and frequency ratios are examined and discussed in detail.

Keywords: exact solution, nonlocal modified sinusoidal shear deformation theory, out of plane vibration, moderately thick rectangular plate

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Authors: A. Nicknam, N. Eftekhari, A. Mazarei, M. Ganjvar

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This article presents an alternative collapse capacity intensity measure in the three elements form which is influenced by the spectral ordinates at periods longer than that of the first mode period at near and far source sites. A parameter, denoted by β, is defined by which the spectral ordinate effects, up to the effective period (2T_1), on the intensity measure are taken into account. The methodology permits to meet the hazard-levelled target extreme event in the probabilistic and deterministic forms. A MATLAB code is developed involving OpenSees to calculate the collapse capacities of the 8 archetype RC structures having 2 to 20 stories for regression process. The incremental dynamic analysis (IDA) method is used to calculate the structure’s collapse values accounting for the element stiffness and strength deterioration. The general near field set presented by FEMA is used in a series of performing nonlinear analyses. 8 linear relationships are developed for the 8structutres leading to the correlation coefficient up to 0.93. A collapse capacity near field prediction equation is developed taking into account the results of regression processes obtained from the 8 structures. The proposed prediction equation is validated against a set of actual near field records leading to a good agreement. Implementation of the proposed equation to the four archetype RC structures demonstrated different collapse capacities at near field site compared to those of FEMA. The reasons of differences are believed to be due to accounting for the spectral shape effects.

Keywords: collapse capacity, fragility analysis, spectral shape effects, IDA method

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

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Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

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Authors: K. Rana, H.A.Saeed, S. Zahir

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Inter Laminar Shear Stress (ILSS) is a main key parameter which quantify the properties of composite materials. These properties can ascertain the use of material for a specific purpose like aerospace, automotive etc. A modelling approach for determination of ILSS is presented in this paper. Geometric modelling of composite material is performed in TEXGEN software where reinforcement, cured matrix and their interfaces are modelled separately as per actual geometry. Mechanical properties of matrix and reinforcements are modelled separately which incorporated anisotropy in the real world composite material. ASTM D2344 is modelled in ANSYS for ILSS. In macroscopic analysis model approximates the anisotropy of the material and uses orthotropic properties by applying homogenization techniques. Shear Stress analysis in that case does not show the actual real world scenario and rather approximates it. In this paper actual geometry and properties of reinforcement and matrix are modelled to capture the actual stress state during the testing of samples as per ASTM standards. Testing of samples is also performed in order to validate the results. Fibre volume fraction of yarn is determined by image analysis of manufactured samples. Fibre volume fraction data is incorporated into the numerical model for correction of transversely isotropic properties of yarn. A comparison between experimental and simulated results is presented.

Keywords: ILSS, FEA, micromechanical, fibre volume fraction, image analysis

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Authors: Warunpun Kongsom, Chaiwat Kongsom

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The objective of this study was to investigate the awareness, knowledge and consumer behavior towards organic products in Thailand. For this study, a purposive sampling technique was used to identify a sample group of 2,575 consumers over the age of 20 years who intended or made purchases from 1) green shops; 2) supermarkets with branches; and, 3) green markets. A questionnaire was used for data collection across the country. Descriptive statistics were used for data analysis. The results showed that more than 92% of consumers were aware of organic agriculture, but had less knowledge about it. More than 60% of consumers knew that organic agriculture production and processing did not allow the use of chemicals. And about 40% of consumers were confused between the food safety logo and the certified organic logo, and whether GMO was allowed in organic agriculture practice or not. In addition, most consumers perceived that organic agricultural products, good agricultural practice (GAP) products, agricultural chemicals free products, and hydroponic vegetable products had the same standard. In the view of organic consumers, the organic Thailand label was the most seen and reliable among various organic labels. Less than 3% of consumers thought that the International Federation of Organic Agriculture Movements (IFOAM) Global Organic Mark (GOM) was the most seen and reliable. For the behaviors of organic consumers, they purchased organic products mainly at the supermarket and green shop (55.4%), one to two times per month, and with a total expenditure of about 200 to 400 baht each time. The main reason for buying organic products was safety and free from agricultural chemicals. The considered factors in organic product selection were price (29.5%), convenience (22.4%), and a reliable certification system (21.3%). The demands for organic products were mainly rice, vegetables and fruits. Processed organic products were relatively small in quantity.

Keywords: consumer behavior, consumer knowledge, organic products, Thailand

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Authors: Rajkumar Kolangarakandy

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Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

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Authors: Deepika Sudevan, Patrick Rozycki, Laurent Gornet

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This paper presents the experimental identification of the fatigue limit for pristine and impacted Carbon Fiber Reinforced Epoxy polymer (CFRP) woven composites based on the relatively new self-heating methodology for composites. CFRP composites of [0/90]8 and quasi isotropic configurations prepared using hand-layup technique are subjected to low energy impacts (20 J energy) simulating a barely visible impact damage (BVID). Runway debris strike, tool drop or hailstone impact can cause a BVID on an aircraft fuselage made of carbon composites and hence understanding the post-impact fatigue response of CFRP laminates is of immense importance to the aerospace community. The BVID zone on the specimens is characterized using X-ray Tomography technique. Both pristine and impacted specimens are subjected to several blocks of constant amplitude (CA) fatigue loading keeping R-ratio a constant but with increments in the mean loading stress after each block. The number of loading cycles in each block is a subjective parameter and it varies for pristine and impacted CFRP specimens. To monitor the temperature evolution during fatigue loading, thermocouples are pasted on the CFRP specimens at specific locations. The fatigue limit is determined by two strategies, first is by considering the stabilized temperature in every block and second is by considering the change in the temperature slope per block. The results show that both strategies can be adopted to determine the fatigue limit in both pristine and impacted CFRP composites.

Keywords: CFRP, fatigue limit, low energy impact, self-heating, WRM

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Authors: Kazuma Mizukoshi

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Are electoral politics in contemporary Brazil still local in organization and focus? The importance of this question lies in its paradoxical trajectories. First, often coupled with institutional and sociological ‘barriers’ (e.g. the selection and election of candidates relatively loyal to the local party leadership, the predominance of territorialized electoral campaigns, and the resilience of political clientelism), the regionalization of electoral politics has been a viable and practical solution especially for pragmatic politicians in some Latin American countries. On the other hand, some leftist parties that once served as minor opposition forces at the time of foundational or initial elections have certainly expanded vote shares. Some were eventually capable of holding most (if not a majority) legislative seats since the 1990s. Though not yet rigorously demonstrated, theoretically implicit in the rise of leftist parties in legislative elections is the gradual (if not complete) nationalization of electoral support—meaning the growing equality of a party’s vote share across electoral districts and its change over time. This study will develop four hypotheses to explain the dynamics of party nationalization in contemporary Brazil: district magnitude, ethnic and class fractionalization of each district, voting intentions in federal and state executive elections, and finally the left-right stances of electorates. The study will demonstrate these hypotheses by closely working with the Brazilian Electoral Study (2002-2014).

Keywords: party nationalization, presidential coattails, Left, Brazil

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Authors: Lila Boulekbache-Makhlouf, Fatiha Brahmi

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This study was carried out with the aim of enriching fresh cheese with the food by-products, which are the leaves of shallots and the peels of potatoes. Firstly, the conditions for extracting the total polyphenols using ultrasound are optimized. Then, the contents of total polyphenols PPT , flavonoids and antioxidant activity were evaluated for the extracts obtained by adopting the optimal parameter. On the other hand, we have carried out some physicochemical, microbiological and sensory analyzes of the cheese produced. The maximum total polyphenols value of 70.44 mg GAE gallic acid equivalent / g of dry matter DM of shallot leaves was reached with 40% (v/v) ethanol, an extraction time of 90 min and a temperature of 10 °C. While, the maximum TPP total polyphenols content of potato peels of 45.03 ± 4.16 mg gallic acid equivalent / g of dry matter DM was obtained using an ethanol /water mixture (40%, v/v), a time of 30 min and a temperature of 60 °C and the flavonoid contents were 13.99 and 7.52 QE quercetin equivalent/g dry matter DM, respectively. From the antioxidant tests, we deduced that the potato peels present a higher antioxidant power with the concentration of extracts causing a 50% inhibition IC50s of 125.42 ± 2.78 μg/mL for 2,2-diphényl 1-picrylhydrazyle DPPH, of 87.21 ± 7.72 μg/mL for phosphomolybdate and 200.77 ± 13.38 μg/mL for iron chelation, compared with the results obtained for shallot leaves which were 204.29 ± 0.09, 45.85 ± 3,46 and 1004.10 ± 145.73 μg/mL, respectively. The results of the physicochemical analyzes have shown that the formulated cheese was compliant with standards. Microbiological analyzes show that the hygienic quality of the cheese produced was satisfactory. According to the sensory analysis, the experts liked the cheese enriched with the powder and pieces of the leaves of the shallots.

Keywords: shallots leaves, potato peels, ultrasound extraction, phenolics, cheese

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Authors: Hugo Sampaio Libero, Max de Castro Magalhaes

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The perception of sound radiated from a building floor is greatly influenced by the rooms in which it is immersed and by the position of both listener and source. The main question that remains unanswered is related to the influence of the source position on the sound power radiated by a complex wall-floor system in buildings. This research is concerned with the investigation of vibration transmission across walls and floors in buildings. It is primarily based on the determination of vibration reduction index via experimental tests. Knowledge of this parameter may help in predicting noise and vibration propagation in building components. First, the physical mechanisms involving vibration transmission across structural junctions are described. An experimental setup is performed to aid this investigation. The experimental tests have shown that the vibration generation in the walls and floors is directed related to their size and boundary conditions. It is also shown that the vibration source position can affect the overall vibration spectrum significantly. Second, the characteristics of the noise spectra inside the rooms due to an impact source (tapping machine) are also presented. Conclusions are drawn for the general trend of vibration and noise spectrum of the structural components and rooms, respectively. In summary, the aim of this paper is to investigate the vibro-acoustical behavior of building floors and walls under floor impact excitation. The impact excitation was at distinct positions on the slab. The analysis has highlighted the main physical characteristics of the vibration transmission mechanism.

Keywords: vibration transmission, vibration reduction index, impact excitation, experimental tests

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Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

Abstract:

Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: Rajeshwari Biradar

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Background: The anecdotal evidences indicate that utilization of HIV services especially in Government facilities is affected by stigma and discrimination among HIV positive female sex workers (FSWs) in Karnataka. To our knowledge, there is no quantitative study on this issue. In this study an attempt is made to examine these aspects among positive FSWs exposed to prevention programs. Methods: This is a cross‐ sectional quantitative survey of HIV positive FSWs in the 3 districts of northern Karnataka using a structured questionnaire. The list of HIV Positive FSWs was organized by stratification, and 607 positive FSWs were selected using a systematic random selection. The data were analyzed using both bivariate and multivariate statistical techniques. Results: Half of the sex workers (52%) are traditional (devadasi, dedicated to the temple), 22% are widowed and the mean age is 33 years. The FSWs practice sex work on an average 13 days a month with 2.3 clients per day and was in sex work for about 13 years. Almost all of them (97%) used condom with the clients they had on the last day of sex work. About 74% were ever registered in the ART center and 47% of them reported being ever on ART, of which 6% dropped out. Multivariate results support the hypothesis that the interventions addressing stigma and discrimination enabled accessing health services in the government facilities (AOR=1.37; p=0.17). Conclusions: Based on the results of the study, programs addressing stigma, discrimination and positive prevention can be implemented in places where government health services are not utilized by HIV positive FSWs. However, the study may be limited by the fact that majority of the FSWs entered into sex work through the traditional devadasi system, which may not be the case in other parts of India.

Keywords: sex work, HIV/AIDS, female sex workers, health

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Authors: Ma. Manna Farrel B. Pinto

Abstract:

As global industrialization progresses, the environment remains to be at risk of disturbances brought by developments of cities and communities. Impacts of flourishing industries such as tourism require rapid growth of establishments and may threaten ecosystems and natural resources. Puerto Galera as a biosphere reserve and declared as the Center of the World’s Center of Marine Shorefish Biodiversity is on the brink of ecological deterioration as tourism further develops in its coastal areas. Apparently, attempts were initiated to establish a baseline for designation of protection in the economic and coastal marine zones of Puerto Galera but continuity of its implementation and coordination of concerned units remains deficient. Indications of eutrophication have been observed based on water quality analysis although parameter values still comply with the national standards for coastal waters. Water quality data, biodiversity and hydrodynamic information, gathered from studies, and local government units were analysed to assess the condition of the coast as well as acting policies implemented by the local authorities. Sources of contaminants were also located in its three main communities, and their shores wherein in recommendations for installing wastewater treatment facilities and further improvement of policies of waste discharge must be addressed. With a conceptual framework proposed in the study, a comprehensive data analysis and coordinated management are necessary to form an integrated coastal management for further protection and preservation of the sustainable coastal marine ecosystem of Puerto Galera.

Keywords: coastal management, environmental management, integrated resource management, Puerto Galera

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Authors: Brandon Foggo, Nanpeng Yu

Abstract:

Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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